Clustering of spectral patterns based on EMD components of EEG channels with applications to neurophysiological signals separation

Authors:
Tomasz M. Rutkowski;Andrzej Cichocki;Toshihisa Tanaka;Anca L. Ralescu;Danilo P. Mandic
Affiliations:
RIKEN Brain Science Institute, Wako-shi, Saitama, Japan;RIKEN Brain Science Institute, Wako-shi, Saitama, Japan;Tokyo University of Agriculture and Technology, Tokyo, Japan and RIKEN Brain Science Institute, Wako-shi, Saitama, Japan;Computer Science Department, University of Cincinnati, Ohio;Department of Electrical and Electronic Engineering, Imperial College London, UK
Venue:
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Year:
2008

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Analyses of instantaneous frequencies of sharp I, and II electroencephalogram waves for epilepsy

WORLD-EDU'12/CIT'12 Proceedings of the 6th international conference on Communications and Information Technology, and Proceedings of the 3rd World conference on Education and Educational Technologies

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Abstract

The notion of information separation in electrophysiological recordings is discussed. Whereas this problem is not entirely new, a novel approach to separate muscular interference from brain electrical activity observed in form of EEG is presented. The EEG carries brain activity in form of neurophysiological components which are usually embedded in much higher in power electrical muscle activity components (EMG, EOG, etc.). A novel multichannel EEG analysis approach is proposed in order to discover representative components related to muscular activity which are not related to ongoing brain activity but carry common patterns resulting from non-brain related sources. The proposed adaptive decomposition approach is also able to separate signals occupying same frequency bands what is usually not possible with contemporary methods.